Novel Genomic Tools to Assess Fish Diet and Prey Quality and in the Choptank River

Principal Investigator:

Louis Plough

Start/End Year:

2018 - 2020


Horn Point Laboratory, University of Maryland Center for Environmental Science

Co-Principal Investigator:

Jamie Pierson, Horn Point Laboratory, University of Maryland Center for Environmental Science


Strategic focus area:

Sustainable fisheries and aquaculture


Zooplankton are critical food sources for marine fish, and climate-driven changes in their abundance, diversity, and quality can have profound effects on larval recruitment and fisheries productivity in coastal oceans and estuaries. Despite the importance of prey for understanding variation in fisheries recruitment, accurate identification of zooplankton species remains challenging and a lack of information on prey quality and prey selectivity by fish may hinder the discovery of relationships between zooplankton and fish productivity. In Chesapeake Bay, two copepods, Acartia tonsa and Eurytemora carolleeae, are critical components of bay anchovy (Anchoa mitchili), larval striped bass (Morone saxatilis), and other fish diets. However, the relative prey quality of these and other zooplankton species in Chesapeake Bay is poorly characterized, and current approaches to quantify zooplankton lack sufficient taxonomic resolution to distinguish known cryptic lineages in A. tonsa, which may differ substantially in prey quality. Novel approaches are needed to resolve taxonomy among zooplankton, to determine diet selectivity, and to measure prey quality, information which will advance our understanding of how the prey field affects recruitment variation in these commercially and ecologically significant species.

In this proposal, we seek to characterize how changes in environmental variables influence fish diets and zooplankton abundance, distribution, and quality (lipids) in the Choptank River, using cutting-edge genomic barcoding and lipid analysis approaches. We will quantify the diversity of zooplankton in the field and in fish gut contents, placing particular focus on the two dominant prey items, E. carolleeae and A. tonsa. For those target prey species, we will track variation in prey quality based on individual size and lipid content. By synthesizing gut contents, zooplankton composition and diversity, prey quality, and environmental data, we will produce novel zooplankton prey indices informed by the biology of the prey items and their importance in observed fish diets. These indices will be compared with fisheries productivity data from the MD DNR Juvenile Recruitment Indices, using data collected for this project and with historical zooplankton datasets (where possible) in step-wise regression models. Our goal is to determine which measurements of abundance and food quality are most important for developing useful indices for fisheries management, and to assess the efficacy of a genomic metabarcoding approach for characterizing zooplankton composition for monitoring efforts. To that end, we will specifically compare the cost and accuracy as well as the taxonomic resolution of the results of metabarcoding to more traditional microscopic identification and enumeration.

A major outcome of this project is hoped to be the implementation of these novel techniques for future monitoring efforts in the Chesapeake Bay region, which will be communicated to policymakers, managers, and stakeholders from MD DNR and NOAA through a workshop and best-practices document. Additionally, a new partnership with Chesapeake College will provide opportunities for undergraduates to engage in a comprehensive field/lab research experience, learning cutting-edge molecular techniques in zooplankton and fisheries ecology and providing college credit through an internship class.


They Are What They Eat: New Genomic Tools Help Define the Relationship Between Zooplankton Prey Quality and Fish Recruitment

Recap: Maryland Sea Grant-supported researchers used the novel method of genomic meta-barcoding to more precisely identify zooplankton species, as well as the contents of larval fish guts, in samples from the Choptank River. The work will help scientists and managers better understand the key relationship between zooplankton type, abundance, and diversity and fish recruitment.

Relevance: Zooplankton are a foundation of the Chesapeake Bay’s food webs. These mostly microscopic animals are a vital food source for larval fish (though fish larvae themselves are considered plankton at this stage of their lives). Yet, despite their importance to the growth and recruitment of species such as striped bass, scientists face challenges in understanding the relationship between zooplankton diversity and fish productivity. Identifying zooplankton species can be difficult and time consuming, as is understanding which are the highest quality and most frequently chosen prey among different larval fish, and how environmental factors—such as water quality and effects of climate change—influence zooplankton abundance and diversity. Finding a more efficient way to accurately identify zooplankton to assess diversity and abundance, as well as learning which fish are eating what zooplankton and when, can help fisheries managers better understand the key relationship between zooplankton and fish recruitment. 

Response: Between April and September over two years, researchers—including a Sea Grant Fellow and five undergraduates from Chesapeake College—took zooplankton and larval fish samples at three Choptank River sites near Maryland Department of Natural Resources water quality monitoring stations. They extracted 52zooplankton DNA samples and analyzed them via genomic metabarcoding, through which multiple species in a single sample can be genetically identified based on their unique DNA sequences. Researchers identified as many as 347 distinct taxa, including so-called cryptic species—those that look identical but are genetically different. Researchers also compared novel metabarcoding to traditional morphological species identification in terms of time, cost, and accuracy. The next step—using metabarcoding to precisely analyze larval fish gut contents and help determine feeding selectivity—is underway (COVID-19 restrictions delayed this research in 2020).

Result: The comparison of identification methods found that while both showed about the same taxonomic resolution, metabarcoding resulted in more identification to the species level than traditional morphological identification. Also, while metabarcoding costs slightly more, it requires far less time to process samples. The research confirmed that as DNA sequence databases expand, metabarcoding can help scientists more quickly and precisely identify zooplankton species and diversity in the Bay. The Sea Grant Fellow is developing a web-based application to help users analyze which identification process will work best for their project based on parameters including processing time and materials cost. Researchers plan to share their results at a 2021 workshop with federal and state fisheries officials, as well as develop a best-practices document on these methods. This research also established a new partnership with Chesapeake College that gives undergraduates long-term field and lab experience with cutting-edge molecular technologies in zooplankton and fisheries ecology.

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